This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In order to provide a completely automated process for collecting data from pre-screened crystals, the samples must be repositioned on the goniometer in an automated fashion. Repositioning of the sample using video analysis of the sample was explored. Several software packages developed at other synchrotrons and new algorithms were tested. This project utilizes indexing information from diffraction images and the results from video analysis. The correct phi for remounting a crystal is predicted from a video analysis using two diffraction images from the crystal before removal and two images after remounting the crystal. We have tested ~600 crystals and further fine tuning is in progress. Results indicate that the combination of indexing and video alignment should allow automated crystal queuing at a very high rate of success.